3D cameras using structured light are a modified version of a stereo camera which uses two or more identical cameras to obtain 3D information. Unlike the stereo camera, the 3D camera includes a camera and a projecting unit such as a beam projector instead of having two identical cameras. Such a structured light based camera system illuminates a predetermined pattern on an object using the projecting unit, captures an image of the object with the pattern illuminated thereon using an image capturing unit such as a camera, and obtains 3D information by analyzing the obtained pattern.
Although a stereo camera system passively uses features of an image, the structured light based camera system actively uses the pattern illuminated from the projecting unit as features. Therefore, the structured light based camera system has advantages of a fast processing speed and a high spatial resolution. Due to the advantages, the structured light based camera system has been widely used for object modeling/recognition, three dimensional (3D) ranging, industrial inspection, and reverse engineering. Particularly, in an intelligent robot engineering field, a home service robot needs a structured light based camera system for the large scale of 3D data for workspace modeling because an ordinary stereo camera system cannot obtain 3D information from a plain and simple environment which does not have sufficient characteristic information or no background color variation, that is, an environment with no feature point.
In the structured light camera system, the precision of 3D data depends on discrimination of patterns, which are illuminated from a projector, from an image. However, it is difficult to discriminate patterns in a real environment that dynamically varies in time or under various object conditions.
For example, it is difficult to identify patterns illuminated on an object having low reflectivity such as a black cloth because a camera cannot accurately capture the patterns illuminated on the black cloth. On the contrary, it is also difficult to identify patterns illuminated on an object having high reflectivity such as an opalescent white object because the patterns show spread phenomenon (saturation) in a captured image due to the opalescent characteristic.
In general, the structured light based camera controls a camera iris to receive more light for an object having low reflectivity. On the contrary, the structured light based camera controls a camera iris to receive limited light in order to prevent spread phenomenon (saturation) for an object having high reflectivity.
Difficulty of pattern discrimination in real environment divides into two kinds. First, it is difficult to control an exposure level according to an object because a real environment includes various objects each having different reflectivity due to colors and textures of objects. Secondly, different exposure levels are required according to the illumination of a peripheral environment. For example, an exposure level of a structured light based camera must be differently controlled when the structured light based camera operates in a bright environment from when the structured light based camera operates in a dark environment.
Although it is required that an exposure level must be adjusted properly in dynamically-varying environmental factors in order to accurately identify patterns, most of researches for structured light based camera systems have been progressed under assumptions of fixed environmental factors with constant surrounding light. Therefore, there is a demand for developing a technology for dynamically controlling an exposure level of a camera according to change of various environmental factors, for example, whenever time, position, and distance changes with respect to a service robot's mission.